Abstract

Programming by Demonstration (PbD) covers methods by which a robot learns new skills through human guidance and imitation. PbD has been a key topic in robotics during the last decade that includes the development of robust algorithms for motor control, motor learning, gesture recognition and the visual-motor integration. Nowadays, PbD deals more with learning methods than traditional approaches, and frequently it is referred to as Imitation Learning or Behavioral Cloning. This work will review and analyse existing works in order to create a taxonomy of the elements that constitute the most relevant approaches in this field to date. We intend to establish the categories and types of algorithms involved so far in PbD and describing their advantages and disadvantages and potential developments.